24results about How to "Eliminate false positives" patented technology

The invention relates to the technical field of Internet of Things and artificial intelligence, in particular to a real-time dynamic sensing method based on artificial intelligence, which comprises the following steps: S1, a multi-source data acquisition step: synchronously acquiring multi-dimensional real-time dynamic data of a user through a plurality of heterogeneous sensors deployed in a monitoring space, the sensor at least comprises a falling monitoring millimeter wave radar used for monitoring human body existence, a sign monitoring millimeter wave radar used for monitoring heart rate and breath, a sleep monitoring millimeter wave radar or an AI intelligent mattress used for monitoring on-bed / off-bed states and body positions, and an AI intelligent camera used for monitoring behaviors. According to the real-time dynamic sensing method based on artificial intelligence, false alarms possibly generated by a single sensor are effectively eliminated through multi-modal data cross validation. For example, a millimeter wave radar and an AI camera perform dual confirmation on a fall event, and the accuracy is far higher than that of a single technology.

The application belongs to the technical field of laser measuring instruments, and particularly relates to a laser measuring instrument and method for plate conveying rollers, which are easy to be interfered by intermittent and random roller surface stains, leading to detection failure or false reporting, and the following scheme is proposed, which comprises a detection platform, and two linear guides are arranged on one side of the detection platform. The laser measuring instrument and method for plate conveying rollers disclosed by the application have the advantages that through the fusion of laser and visual double sensing data, stains and real damage can be intelligently distinguished, and in-situ cleaning and re-measurement verification are combined, so that false reporting and missed detection are fundamentally eliminated, the data is absolutely reliable, the traditional separated multi-link detection, shutdown, manual investigation and cleaning are integrated into a continuous process of online, automatic and one-time completion, the non-scheduled downtime is greatly reduced, and the effect of changing from passive maintenance to predictive maintenance is achieved.

The present application belongs to the technical field of photovoltaic equipment monitoring fault early warning, and relates to a photovoltaic equipment cluster benchmarking analysis and implicit fault early warning method and system. The system collects basic parameters and implicit associated data of photovoltaic equipment through a data acquisition module to ensure data comprehensiveness and timeliness. Through a data fusion module, the collected data is processed and fused to generate a standardized data sequence. Through a cluster benchmarking module, the photovoltaic equipment is divided into different clusters, a group health benchmark is constructed, and the model accuracy is improved through individual difference calibration. Through a dynamic early warning module, early warning information is generated, and a basis is provided for subsequent fault troubleshooting. Through an intelligent operation and maintenance module, early warning is prioritized and an operation and maintenance scheme is generated, which is pushed to operation and maintenance personnel for optimization guidance. The present application can realize accurate benchmarking analysis and implicit fault early warning of photovoltaic equipment clusters, and reduce the failure rate.

The application discloses a kind of river health state evaluation and early warning method and system, belong to ecological environment monitoring and automation control technical field, which comprises: obtaining the real-time monitoring data of river monitoring point;According to real-time monitoring data, the final water quality grade of current time is evaluated, and the diurnal comprehensive index of current time is calculated;Obtain the historical reference diurnal comprehensive index based on historical monitoring data, and calculate the dynamic early warning threshold according to the historical reference diurnal comprehensive index and the final water quality grade of current time;The diurnal comprehensive index of current time is compared with the dynamic early warning threshold, when the diurnal comprehensive index of current time is lower than dynamic early warning threshold, generate early warning information, and generate control instruction according to the comparison result, to adjust the operating parameter of front-end monitoring equipment.The present application provides a complete technical solution of precision, intelligentization and automation for the long-term supervision of "Sewage Zero Direct Discharge Area".

The invention provides a diagnosis and treatment full-cycle intelligent closed-loop management method and system, and relates to a data processing technology and analysis of early-stage data uploaded by an electronic information system, the electronic information system can be a hospital information system, an electronic medical record system, a laboratory information system and the like, permission information is responded, and a state comparison structure is constructed; constructing a standard comparison structure based on the reference data, performing branch comparison on the state comparison structure and the standard comparison structure, and generating comparison information for early warning of high-risk medium and high risks; executing corresponding stage operation based on the progress stage of the comparison information, wherein the progress stage comprises a preoperative stage, a middle stage and a later stage of anesthesia induction; the method comprises the steps of performing visualization processing on perioperative period management and stage operation corresponding to the perioperative period management, generating a visual time sequence chain, receiving change information of an electronic information system user side on the visual time sequence chain, generating a visual feedback chain and performing medium-high risk early warning.

The application relates to the technical field of urban underground pipe network safety monitoring, and discloses a wave corrugation compensator leakage positioning method and system based on an Internet of Things, which is applied to an Internet of Things system comprising a cloud server and a plurality of sensing nodes, and the sensing nodes are installed in the interlayer space of the wave corrugation compensator. The method comprises the following steps: collecting pressure and temperature data of the interlayer space by the nodes at a low frequency, triggering an adjacent node to enter a high-frequency acoustic sampling mode when the pressure change rate is greater than a dynamic threshold value; collecting an acoustic emission signal, filtering mechanical noise through a noise reduction model, and extracting fluid jet noise characteristics; performing cross-correlation analysis on the acoustic signals between the nodes to calculate the actual sound wave conduction distance, and verifying whether real leakage occurs by comparing with a physical topological distance; and finally evaluating the leakage grade according to the steady-state peak value of the pressure data and the acoustic frequency energy data, and outputting device coordinate information. The application has both ultra-low power consumption and strong anti-interference capability, and realizes accurate element-level leakage positioning.

The invention discloses a multi-mode esophageal cancer identification method and system based on frequency characteristics, and relates to the technical field of medical image processing, and the method comprises the steps: synchronously collecting a photoacoustic echo sequence, a shear wave elastic displacement sequence and an optical coherence tomography image sequence, and packaging the sequences into a homologous frame index data set according to a frame index number; a frequency event graph with unit numbers as nodes is constructed according to the regular grid adjacency relation of the frequency unit graph, homonymous coupling judgment and axial propagation continuity judgment are carried out on the three-mode frequency event sequence of each node, and a suspected lesion unit set and a connected component identifier are obtained. According to the method, the homodromous coupling judgment and the axial propagation continuity judgment are carried out on the multi-modal frequency event sequence of the nodes on the graph, the abnormal sites with the multi-modal frequency characteristics in collaborative change are screened out from massive units, the false positive caused by random noise or isolated abnormality is eliminated, and the recognition specificity is remarkably improved.

The application discloses a kind of based on acoustic feature converter interturn short circuit detection method and system, method includes the following steps: constructing converter three-dimensional simulation model, setting electromagnetic-thermal-force-acoustic multi-physical field coupling, extracting temperature, equivalent stress and sound pressure level and normalizing processing, determine peak region and divide peak connected region;The spatial consistency factor between peak connected region is calculated, and acoustic sensitive area is identified;The acoustic thermal force joint sensitivity in acoustic sensitive area is calculated, to maximize total acoustic thermal force joint sensitivity as target, solve optimal monitoring point arrangement scheme;With optimal monitoring point arrangement scheme, monitoring point arrangement is carried out, the acoustic characteristic vector under different working conditions and actual working condition is calculated, and the actual state of converter under actual working condition is determined.The present application realizes the high-precision detection, accurate positioning of converter interturn short circuit fault by multi-physical field information, combined with acoustic sensitive area identification, monitoring point optimization arrangement and working condition matching analysis.

This invention relates to the field of document processing and text analysis technology, and discloses a text comparison method based on a sliding window and a dynamically expanding KMP algorithm. This method sets a minimum matching threshold, uses a sliding window with a step size of 1 to extract substrings from the document character by character as matching patterns, and then employs an improved KMP algorithm for scanning and matching to fully preserve the actual position information of characters in the original text. This effectively avoids positional deviations and context loss caused by preprocessing in traditional methods. After a successful initial match, the system automatically enters a dynamic expansion phase, extending the matching range character by character until continuous matching is no longer possible, thereby determining the longest repeating text segment. After matching, a dedicated result merging module intelligently merges and structures adjacent or overlapping matching segments, ultimately outputting a clear result containing the original start and end positions, repeating content, and length information. These operations significantly improve the efficiency and accuracy of large-scale document comparison.

This disclosure relates to a control method, device, and vehicle for contactless anti-pinch protection of vehicle windows, including: acquiring spatial motion status parameters of an obstacle relative to an onboard radar sensor on the window closing path, and obtaining the real-time position of the obstacle based on the spatial motion status parameters; generating movement parameters of the obstacle based on the real-time position at multiple time points; determining whether the obstacle meets threat conditions based on the spatial motion status parameters and movement parameters, wherein the threat conditions are used to characterize the risk of the obstacle being pinched; and triggering the window to perform anti-pinch operation when it is determined that the obstacle meets the threat conditions. This disclosure relies on the non-contact active sensing characteristics of radar, actively emitting electromagnetic waves for detection. Tens to hundreds of milliseconds before the glass and obstacle collide, the radar has already detected the obstacle's intrusion path, thereby achieving pre-collision intervention. This represents a technological upgrade from traditional passive motor load detection to active spatial sensing, allowing for early risk detection without physical contact with the obstacle.

The application discloses a kind of based on efficient reinforcement fine tuning and rule check multi-modal industrial intelligent detection method and system, method includes: S1.to industrial detection data is divided, and reference sample library and industrial acceptance rule base are constructed;S2.in frozen multi-modal base model, introduce interlayer collaborative adjustment module, and build feature space;S3.in feature space, extract locatable abnormal evidence, and output structured detection result that can be directly accessed in industrial acceptance rule base and check;S4.structurized detection result is input to industrial acceptance rule base and is checked, obtains industrial rule check result;S5.based on industrial rule check result, the related parameter of interlayer collaborative adjustment module is reinforced fine tuning, obtains multi-modal detection model;S6.based on multi-modal detection model, the abnormal detection and industrial acceptance determination of sample to be detected on production line are carried out, obtains final detection result.

This invention relates to the field of electronic digital data processing and discloses a method for generating computable task semantics from SOP text for flight training. The method includes: parsing the original script to extract key elements and constructing task nodes containing target states, parameter tolerance ranges, and behavioral rules; establishing directed dependencies between nodes to generate a task semantic graph; calculating a semantic execution score factor representing the degree of convergence of the operational intent towards the target state based on the evolution trend of the controlled entity feature state vector within a preset time window; and using the numerical evolution characteristics of the score factor satisfying the convergence criterion as the basis for triggering topological migration of the task semantic graph. This invention replaces instantaneous threshold comparison with temporal residual evolution judgment, eliminating the spatiotemporal mismatch between discrete semantic commands and continuous telemetry data streams, and improving the system's fault tolerance for non-standard phase operation recognition.

This invention discloses a method and system for detecting life jacket wearing at port berths. The method includes: constructing a monitoring area and deploying computing nodes; training a YOLOv8 model for initial and secondary detection, a ResNet model for illumination classification, a Uformer model for rain and fog recovery, and a YOLOv8 model for semantic segmentation; performing illumination scene recognition on the acquired images and adaptively selecting the corresponding preprocessing method; using the initial detection results, for personnel targets with insufficient pixel size, predicting their position by tracking and calculating the magnification factor, controlling the PTZ camera to magnify and perform secondary detection for confirmation; using the semantic segmentation results to determine whether the personnel are located in the land-based work area; and combining target tracking, triggering an alarm only when the personnel are not wearing life jackets, are located on land, and their status continuously exceeds a threshold. The system includes an intelligent PTZ camera, a management platform, and a processing unit. This invention solves the problems of difficult identification of small targets at long distances, poor adaptability to complex illumination, and high false alarm rate due to rule-based methods.

This invention relates to the field of power equipment condition monitoring, specifically to a method and system for monitoring the operating status of electricity meter boxes. An electricity meter box operating status monitoring system includes: a status perception module, an intelligent analysis module, a diagnosis and evaluation module, and an operation and maintenance decision-making module. This invention achieves accurate modeling and dynamic adaptation of the operating status of electricity meter boxes by constructing a personalized dynamic health benchmark model and combining it with real-time acquisition of multi-dimensional sensor data. This effectively eliminates the misjudgment problem caused by fixed threshold monitoring under different seasons, time periods, and load conditions, thereby improving the accuracy of anomaly identification and the system's environmental adaptability.

This invention discloses a high-voltage switchgear with insulation monitoring function, including a cabinet, a busbar compartment and a cable compartment respectively arranged on the cabinet, a support frame on the cabinet, a hollow plate on the support frame, a gas supply pipe one on the hollow plate, a gas supply pipe two connected to the gas supply pipe one, a housing connected to the gas supply pipe two, and a suction nozzle on the housing; one end of the gas supply pipe one is connected to a gas supply mechanism; and a monitoring mechanism is arranged on the hollow plate. This invention achieves four major functions—active sampling monitoring, gas chamber vacuuming, old gas recovery, and new gas recharging—through the precise switching of three intelligent control valves. The sulfur hexafluoride compressor, vacuum pump, and sulfur hexafluoride storage tank are all integrated outside the switchgear body. During power outage maintenance, there is no need to move the bulky external recovery device, nor to perform complex pipeline connections and leak detection; the system can automatically execute the complete "vacuuming → recovery → recharging" process.

The application discloses a photovoltaic water pump inverter operation state analysis method and system, relates to the photovoltaic system monitoring technical field, and is used for solving the problem of high false alarm rate of fault identification under complex working conditions. First, the direct current side steady-state power supply component and the dynamic ripple component are extracted through frequency domain separation to construct equivalent impedance and mechanical vibration characteristics. Then, the power-impedance sensitivity is analyzed to define the power supply side gradient characteristic interval. At the same time, the linear coupling degree of electromechanical energy is used to accurately distinguish the linear drift of light and the physical nonlinear distortion. Finally, based on the sensitivity interval and the coupling degree evolution state, multi-dimensional logic judgment is performed to realize the accurate classification of the normal, overload stuck and no-load dry running state of the water pump motor, and the fault diagnosis precision and environmental adaptability of the photovoltaic power supply system are improved.

The application relates to the technical field of ultrasonic metering, and particularly provides an ultrasonic meter zero drift online calibration method, an ultrasonic water meter and a medium. The method comprises the following steps: initializing parameters and single-time static water statistics; collecting meter forward flow and reverse flow time of flight, calculating a reverse-to-forward flow time difference, updating a time difference average value, a variance cumulative value and a time difference sample number through an iterative statistical algorithm; judging whether the variance and the time difference average value are effective; carrying out difference check on the current time difference average value and a historical time difference average value, updating the historical time difference average value when a continuous difference threshold is met; when the average value calculation frequency reaches a maximum average value calculation frequency, accumulating a static water frequency and resetting the average value calculation frequency; when the static water frequency reaches a maximum static water frequency, updating the zero drift by updating the historical time difference average value, and completing online updating of the ultrasonic meter. The application can distinguish static water and small flow water, eliminate misjudgment caused by slight leakage, and enhance the robustness of zero drift calculation.

The application discloses a circulating water pressure low diagnosis method, relates to the technical field of fluid delivery systems, and comprises the following steps: collecting a water pressure value in a circulating water pipe network in real time; when the monitored water pressure value is less than or equal to a preset first pressure threshold value, calculating a water pressure drop rate within a first preset time period before the water pressure value is lower than the first pressure threshold value; if the water pressure drop rate is greater than a normal fluctuation rate threshold value and less than a mutation rate threshold value, starting active pressurization diagnosis, controlling a pressurization station or a variable frequency water pump to pressurize the circulating water pipe network once, and monitoring a pressure response characteristic of the water pressure value after the pressurization is stopped; and judging whether a pipeline leaks or not according to the pressure response characteristic. Through active pressurization diagnosis, the application can effectively eliminate false positives caused by normal water use or working condition changes, the judgment result is more reliable, and the technical defects that passive detection methods are prone to misjudgment under complex working conditions are effectively overcome.

This application relates to a control method, apparatus, computer equipment, storage medium, and computer program product for a sweeping robot. The method includes: when the pressure sensor detects a collision feedback signal, acquiring the time-of-flight information of the ultrasonic signal to the ground via a first ultrasonic sensor; and acquiring gyroscope information corresponding to the gyroscope signal via a gyroscope; determining whether the sweeping robot body is in an unstable state based on the time-of-flight information and the gyroscope information; if the sweeping robot body is in an unstable state, determining that the pressure sensor does not generate a false alarm. This method can improve the accuracy of data processing of the pressure sensor signal by the sweeping robot's main control unit.

The application discloses a method and system for assisting in determining the grade of brain glioma, and belongs to the technical field of biological genes and bioinformatics. The method comprises the following steps: obtaining sample information of a patient and pre-processing the sample; performing FISH detection, NGS detection assisted bioinformatics analysis and pathological detection on the sample to obtain N1 FISH detection indexes, N2 NGS detection indexes and N3 pathological detection indexes, and gene variation phenomenon characteristics corresponding to each detection index; and determining the type and grade of brain glioma based on the detection indexes and the gene variation phenomenon characteristics corresponding to one or more of the detection indexes. The application also discloses corresponding systems, electronic devices and computer readable storage media. The NGS sequencing technology is used to replace part of the conventional FISH detection mode, the NGS data is retained, secondary analysis is performed by using the bioinformatics method to obtain new molecular indexes in the guidelines, the detection types and times are reduced, and the detection mode is optimized.

The application discloses a tower crane installation and disassembly intelligent auxiliary method based on multi-modal AI perception and digital twin guidance, and belongs to the technical field of construction machinery construction safety, which comprises the following steps: constructing a standard installation and disassembly operation plan library and matching a current scene process list; collecting multi-source heterogeneous perception data in real time through a multi-modal data acquisition unit; generating a tower crane real-time mapping state by using a physical mechanism constraint of a digital twin model and an error compensation algorithm; outputting standard section accurate alignment guidance and connection state intelligent detection instructions based on the real-time state; constructing a process interlocking mechanism, locking the tower crane action when detecting process violation; establishing a comparison mechanism of risk detection parameters and graded safety threshold values, and executing risk grading active blocking. Through multi-modal perception and digital twin technology, the application realizes quantitative guidance of tower crane installation and disassembly operation, process forced interlocking and graded safety control, and significantly improves the intrinsic safety level of the operation.

This invention discloses a semi-quantitative RT-LAMP method and kit for viral nucleic acid detection based on dispensed lyophilized microspheres and a multi-channel microfluidic chip. The method includes: designing two independent LAMP primer sets (P1 and P2) for each of the SARS-CoV-2 Omicron strain N gene, Zika virus NS5 gene, H1N1 influenza virus M1 gene, and H3N2 influenza virus NP gene; preparing two independent types of lyophilized microspheres by independently mixing RT-LAMP premix containing Bst DNA polymerase and other components with LAMP primer mixture and a lyophilization protectant; and using an N-channel microfluidic chip to perform serial dilutions and parallel RT-LAMP amplification of the same sample, determining the concentration of viral nucleic acid in the sample by the positive / negative inflection points of each channel. This invention is simple to operate, requires no equipment such as a real-time PCR instrument, and is suitable for rapid virus detection in various scenarios.

The application relates to the technical field of smart grids, and discloses an automatic power supply abnormality identification and repair command system, which comprises the following units: a situation monitoring unit which acquires a sequence component current vector of a node and a total current vector of a logical bus, generates a sequence current residual vector by calculating the modulus value deviation between the total current vector and the sequence component current vector; a risk situation assessment unit which calculates a state distribution deviation deterioration rate according to a current fluctuation sequence, and calculates a critical time margin before reaching a power supply logic failure point; a resource allocation unit which calculates a response time delay variable of a response terminal to the node; and a dispatching command unit which outputs a topological safety isolation instruction when the response time delay variable is not lower than the critical time margin, the application adopts sequence current residual logic to improve positioning accuracy, establishes an intervention mechanism between business risk evolution and response resources, realizes predictive command, and avoids resource waste caused by physical damage.

This invention provides a valve core leakage detection tool, belonging to the technical field of valves. The valve core leakage detection tool includes a valve core grinding assembly and a pressure detection assembly. This invention installs the valve sleeve on a lifting platform within the valve core grinding assembly, places the valve core inside the valve sleeve, and connects the lifting platform to a lifting actuator. This allows the relative position of the valve core and valve sleeve to be adjusted when the lifting actuator moves the lifting platform up and down, ensuring that the sealing surfaces or sealing lines of the valve core and valve sleeve are completely aligned. The adjusted valve sleeve and valve core are then transferred as a whole to the pressure detection assembly for sealing and leakage testing. This eliminates false detections caused by non-product quality factors such as improper assembly of the sealing line or sealing surface before testing, thus ensuring the accuracy of the test results.